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I am trying to understanding the algorithm. According to paper, the leaf value is the average value of the gradients of allocated items in the leaf node. However, in here, I found the leaf value is relate to learning rate? Why was that? And how the leaf value is calculated when using gradient estimate method? It would be better to tell my the function file in the source code
This discussion was converted from issue #2633 on April 10, 2024 12:39.
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catboost version: catboost 1.2
Operating System: macos 14.4.1
CPU: M1
GPU: no
I am trying to understanding the algorithm. According to paper, the leaf value is the average value of the gradients of allocated items in the leaf node. However, in here, I found the leaf value is relate to learning rate? Why was that? And how the leaf value is calculated when using gradient estimate method? It would be better to tell my the function file in the source code
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